• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.79-90
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• 2021

This study aims to investigate the relationship between urbanization, economic growth, energy consumption, and CO2 emissions in Indonesia. The data used in the study are time-series data for the period 1985-2017; the data utilized are sourced from World Development Indicators obtained on the World Bank database. The method uses a quantitative approach that applies the vector error correction model based on the Granger causality test. The empirical results reveal that, in the short run, there is evidence that urbanization and energy consumption can causes CO2 emissions, and they also prove that urbanization can cause energy consumption. Also, other findings prove the existence of long-run relationships flowing from energy consumption, economic growth, and CO2 emissions toward urbanization, as well as the existence of the relationship flowing from urbanization, economic growth, and CO2 emissions towards energy consumption. The results of testing the relationship between economic growth and CO2 emissions reveal that the environmental Kuznets curve hypothesis is proven in Indonesia. Thus, policies are needed to limit the impact of urbanization through high awareness-raising to maintain environmental quality and greater use of energy. Also, energy conservation policies are needed in all sectors, especially the electricity, industry, and transportation sectors.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1339-1346
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• 2024

Electrorefining in molten salts is used for purifying actinides. Optimizing electrorefining is key to minimizing processing time and radiological waste. One possible way of improving electrorefining efficiency is using an AC superimposed DC waveform. This waveform has demonstrated potential benefits in aqueous solutions but has never been utilized in a molten metal, molten salt application. This work investigates the effects of using an AC superimposed DC waveform on molten bismuth electrorefining in a molten LiCl-KCl-CaCl2 eutectic. Bismuth has been identified as a potential surrogate for plutonium electrorefining and a potential cathode in electrorefining used nuclear fuel (UNF). All electrorefining runs resulted in a high purity cathode ring and high yield with exception of the run using a low-frequency, high-amplitude superimposed AC waveform, which experienced some contamination and a lower yield. The other three AC superimposed DC runs experienced an average yield 6.7 % higher than the average yield of the DC runs. The electrorefining run using the high-frequency, high-amplitude superimposed AC signal had the highest yield. It is recommended in future studies to investigate the statistical variability of electrorefining yield and current efficiency and the impact of AC superimposed DC waveforms on solidified bismuth anodes.

• Journal of Environmental Impact Assessment
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• v.16 no.2
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• pp.157-168
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• 2007

In case there is a need to run the multi-year urban scale air qulaity model, it is a difficult task due to the computational demand, requiring the statistical approach for the long time atmospheric environmental assessment. In an effort to approach toward long term urban assessment, the sixteen synoptic meteorological conditions are statistically classified from the estimated geostrophic wind speeds and directions of 850 hPa geopotential height field during 2000 ~ 2005. The geostrophic wind directions are subdivided into four even intervals (north, east, south, and west), geostrophic wind speeds into two classes(${\leq}5m/s$ and >5m/s), and daily mean cloud amount into 2 classes(${\leq}5/10$ and >5/10), which result into sixteen classes of the synoptic meteorological cases for each season. The frequency distributions for each 16 synoptic meteorological case are examined and some discussions on how these synoptic classifications can be used in the environmental assessment are presented.

• Atmosphere
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• v.34 no.2
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Land and Housing Review
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• v.11 no.1
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• pp.59-66
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• 2020

This thesis investigates relationship between Stock-to-Flow price and housing starts in Seoul metropolitan form 2008 year to 2019 year. The paper tests the relationship through two time-series models such as a vector error correction model and Dynamic Panel regression model. The model results show evidence of positive correlation between Stock-to-Flow price and housing starts in the long run. By transforming the regional data into a panel data set and running a fixed effects model, we test the explanatory power of PBR on housing starts. The result of VECM confirms that one unit uprising PBR raises up apartment construction by 7.4%. This result supports that PBR is a major factor in choosing a start of housing construct. Base on the result of empirical model, We also suggest that the market self-regulation function of housing providers is operating in the entire metropolitan area market.

• Journal of Distribution Science
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• v.10 no.6
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• pp.7-15
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• 2012

The paper deals with the impact of information and communications technology on carbon emissions and economic growth in South Korea. The quarterly time series data from the first quarter of 1970 to the third quarter of 2010 (163 observations) are collected and retrieved from the Bank of Korea database. The paper examines long-run equilibrium relationships using cointegration techniques and Granger causality with vector error correction models. In directional causality tests, information and communications technology shows highly significant positive effects on economic growth and marginal effect on carbon emissions. Carbon emissions and economic growth exhibit an inverse relationship with each other; that is, carbon emissions have an inverse relation to economic growth and economic growth does not significantly affect carbon emissions in South Korea. We also note possible implications regarding growth policies and the information communications technology and "green" technology sectors for economies in the range represented by Korea's 1970 - 2010 data.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.15-24
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• 2018

The study examines the magnitude of economic spillover and the impact of foreign direct investment (FDI) inflows on the efficiency of the bank industry in China. This study employs unit root tests, cointegration tests and cointegrating regression analysis, including fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR) and dynamic OLS (DOLS) to test the proposed hypotheses. The sample is restricted to the period of time in which monthly data is available and comparable among variables for the period from January 2002 to October 2013 (142 observations). All of the time series data was collected and retrieved from the People's Bank of China, China Monthly Statistics from the National Bureau of Statistics of China, and International Financial Statistics database from International Monetary Fund. The results of the Johansen cointegration test suggest that there is a long-run equilibrium relationship between FDI inflows, foreign exchange rate and banks performance in China. The results of cointegrating regression analysis using FMOLS, CCR and DOLS suggest that M2 supply and FDI inflows are significant at the 0.01 level. The results confirm that FDI inflows in the banking sector are positively related to the increase of banks productivity and performance and short-term loans in China. However, the results suggest that Chinese Yuan currency exchange rate to U.S. dollar is not significant in the banking and financial industry of China.

• Journal of Energy Engineering
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• v.22 no.4
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• pp.370-375
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• 2013

This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.